In silico miRNA prediction in metazoan genomes: balancing between sensitivity and specificity.

ABSTRACT:

Background

MicroRNAs (miRNAs), short approximately 21-nucleotide RNA molecules, play an important role in post-transcriptional regulation of gene expression. The number of known miRNA hairpins registered in the miRBase database is rapidly increasing, but recent reports suggest that many miRNAs with restricted temporal or tissue-specific expression remain undiscovered. Various strategies for in silico miRNA identification have been proposed to facilitate miRNA discovery. Notably support vector machine (SVM) methods have recently gained popularity. However, a drawback of these methods is that they do not provide insight into the biological properties of miRNA sequences.

Results

We here propose a new strategy for miRNA hairpin prediction in which the likelihood that a genomic h

SUBMITTER: van der Burgt A 

PROVIDER: S-EPMC2688010 | biostudies-literature | 2009 Apr

REPOSITORIES: biostudies-literature